hi.
when I use PLS Algorithm, the results show up Latent Variable scores.
On the other hand, when I use PLSc Algorithm, Latent Variable scores is not shown in smartpls3.
I can only see Latent variable correlations and covariances.

May I ask why this kind of situation happen?
If I want Latent variable scores in smartpls3, Should I use only PLS Algorithm?

My model has reflective-reflective 2nd order construct. So I'd like to use two-step approach as my references did.
Therefore, I have to get Latent Variable scores.

If I want Latent variable scores in smartpls3, Should I use only PLS Algorithm?

Yes!

The reason is quite simple: PLSc tries to mimic a common factor model. However, in a common factor model there is not one determinate set of factor (or latent variable) scores that is consistent with the model. There are an infinite many possible scores. The problem is called factor indeterminacy. Therefore, it is not possible to provide a LV score.
PLS on the other side is a method of composites. It explicitly uses the latent variables scores as part of its estimation process. Therefore, you get on set of LV scores that are consistent with your results (i.e., loadings, path coefficients, weights, etc.).

If you have a higher-order construct it would be possible to use the two-stage approach with PLSc only on the second-stage. But you need to manually calculate and set the reliability of the second stage higher-order construct (you can do that by double-clicking on the LV in the path diagramm).